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dc.contributor.authorŠťastný, Jiřícs
dc.contributor.authorŠkorpil, Vladislavcs
dc.contributor.authorBalogh, Zoltáncs
dc.contributor.authorKlein, Richardcs
dc.date.accessioned2021-03-03T11:53:28Z
dc.date.available2021-03-03T11:53:28Z
dc.date.issued2021-02-22cs
dc.identifier.citationApplied Sciences - Basel. 2021, vol. 11, issue 4, p. 1-16.en
dc.identifier.issn2076-3417cs
dc.identifier.other170162cs
dc.identifier.urihttp://hdl.handle.net/11012/196375
dc.description.abstractIn this paper we introduce the draft of a new graph-based algorithm for optimization of scheduling problems. Our algorithm is based on the Generalized Lifelong Planning A* algorithm, which is usually used for path planning for mobile robots. It was tested on the Job Shop Scheduling Problem against a genetic algorithm’s classic implementation. The acquired results of these experiments were compared by each algorithm’s required time (to find the best solution) as well as makespan. The comparison of these results showed that the proposed algorithm exhibited a promising convergence rate toward an optimal solution. Job shop scheduling (or the job shop problem) is an optimization problem in informatics and operations research in which jobs are assigned to resources at particular times. The makespan is the total length of the schedule (when all jobs have finished processing). In most of the tested cases, our proposed algorithm managed to find a solution faster than the genetic algorithm; in five cases, the graph-based algorithm found a solution at the same time as the genetic algorithm. Our results also showed that the manner of priority calculation had a non-negligible impact on solutions, and that an appropriately chosen priority calculation could improve them.en
dc.formattextcs
dc.format.extent1-16cs
dc.format.mimetypeapplication/pdfcs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofApplied Sciences - Baselcs
dc.relation.urihttps://www.mdpi.com/2076-3417/11/4/1921/htmcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectGenetic algorithmsen
dc.subjectgraph-based algorithmen
dc.subjectJob Shop Scheduling Problemen
dc.subjectoptimizationen
dc.titleJob Shop Scheduling Problem Optimization by Means of Graph-Based Algorithmen
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Ústav automatizace a informatikycs
sync.item.dbidVAV-170162en
sync.item.dbtypeVAVen
sync.item.insts2021.04.13 20:54:55en
sync.item.modts2021.04.13 20:14:35en
dc.coverage.issue4cs
dc.coverage.volume11cs
dc.identifier.doi10.3390/app11041921cs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2076-3417/cs
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International